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Whole genome sequencing accurately identifies resistance to extended spectrum β-lactams for major gram-negative bacterial pathogens

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dc.contributor.author Shelburne, Samuel
dc.contributor.author Kim, Jiwoong
dc.contributor.author Munita, Jose
dc.contributor.author Sahasrabhojane, Pranoti
dc.contributor.author Shields, Ryan
dc.contributor.author Press, Ellen G
dc.contributor.author Li, Xiqi
dc.contributor.author Arias, Cesar
dc.contributor.author Cantarel, Brandi
dc.contributor.author Jiang, Ying
dc.contributor.author Kim, Min
dc.contributor.author Aitken, Samuel L.
dc.contributor.author Greenberg, David
dc.date.accessioned 2017-08-29T18:41:42Z
dc.date.available 2017-08-29T18:41:42Z
dc.date.issued 2017
dc.identifier.citation Clin Infect Dis. 2017 May 3 es_CL
dc.identifier.uri http://dx.doi.org/10.1093/cid/cix417 es_CL
dc.identifier.uri http://hdl.handle.net/11447/1616
dc.description.abstract BACKGROUND: There is marked interest in using DNA based methods to detect antimicrobial resistance (AMR) with targeted polymerase chain reaction (PCR) approaches increasingly being incorporated into clinical care. Whole genome sequencing (WGS) could offer significant advantages over targeted PCR for AMR detection, particularly for species where mutations are major drivers of AMR. METHODS: Illumina MiSeq WGS and broth microdilution (BMD) assays were performed on 90 bloodstream isolates of the four most common gram-negative bacteria causing bloodstream infections in neutropenic patients. The WGS data, including both gene presence/absence and detection of mutations in an array of AMR relevant genes, were used to predict resistance to four β-lactams commonly used in the empiric treatment of neutropenic fever. The genotypic predictions were then compared to phenotypic resistance as determined by BMD and by commercial methods during routine patient care. RESULTS: Out of 133 putative instances of resistance to the β-lactams of interest identified by WGS, only 87 (65%) would have been detected by a typical PCR based approach. The sensitivity, specificity, positive and negative predictive values for WGS in predicting AMR were 0.87, 0.98, 0.97, and 0.91 respectively. Using broth microdilution as the gold standard, our genotypic resistance prediction approach had a significantly higher positive predictive value compared to minimum inhibitory concentrations generated by commercial methods (0.97 vs. 0.92, P = 0.025). CONCLUSIONS: These data demonstrate the potential feasibility of using WGS to guide antibiotic treatment decisions for patients with life-threatening infections for an array of medically important pathogens. es_CL
dc.format.extent 1 es_CL
dc.language.iso en_US es_CL
dc.publisher Oxford University Press es_CL
dc.subject antimicrobial resistance es_CL
dc.subject bacteremia es_CL
dc.subject gram-negative bacteria es_CL
dc.subject neutropenic fever es_CL
dc.subject whole genome sequencing es_CL
dc.title Whole genome sequencing accurately identifies resistance to extended spectrum β-lactams for major gram-negative bacterial pathogens es_CL
dc.type Artículo es_CL


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